Written by Jim Oskins from Minitab shares a real-world use case where a government agency turned 60,000+ nitrate tests into actionable insights, cutting analysis time from months to minutes. These tests are needed to quickly identify the cause of nitrate contamination in groundwater near large farms, to ensure groundwater near residential areas did not get exposed to nitrate.
They used predictive modeling and automated machine learning tools like MARS, CART, and Random Forests to uncover hidden patterns and guide smarter decisions.
A Root Cause Analysis revealed the underlying factors and timeframes behind the spikes in contamination.
This resulted in predictive models that were deployed online, allowing individuals to assess water quality risks based on their specific conditions.
Download the 1-page case study at https://info.minitab.com/hubfs/UseCase-NitrateContaminatedWaterControl.pdf